class_docstr: Condition checking a `HyperParameter`'s value is in a list of values.
  
  It specifies a condition that a `HyperParameter`'s value is in a list of
  values. It can be used as the condition to activate another
  `HyperParameter` for the `Trial`.
  
  Example:
  
  ```python
  a = Choice('model', ['linear', 'dnn'])
  condition = Parent(name='model', value=['dnn'])
  b = Int('num_layers', 5, 10, conditions=[condition])
  ```
  
  Args:
      name: A string, the name of the `HyperParameter` to use in the
          condition.
      values: A list of values of the `HyperParameter` to activate the
          condition.
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code: def get_config(self):
      return {"name": self.name, "values": self.values}
  
file_path: keras-tuner/keras_tuner/engine/conditions.py
imports: import abc
  import six
  from keras_tuner import protos
  from keras_tuner import utils
label_desc: Use image node_id 4 for calling the Parent obj's underlying member method code with example usage: obj.get_config() and returns: dict